Full R Bioconductor Training

Day 1

Topic 1 : Introduction to bioinformatics

• What is bioinformatics
• Types of online databases and online tools
• Genomics resources
• Protenomics resources

Topic 2 : Introduction to bioConductor

• BioConductor Website
• installing BioConductor in R
• Bioconductor packages, vignettes, tutorials
• Bioconductor datasets(biocViews)

Topic 3 : Databases in BioConductor

• Annotation Hub
• biomarts (online biomarts)
• Genomic (full genomes)
• GEOquery (NCBI Gene expression Omnibus) & ArrayExpress
• KEGG (Kyto Encyclopedia for Genes and Genomes)
• Gene libraries

Topic 4 : Data files in BioConductor

• Data containers
• Importing data types
• Downloading DNA
• Manipulating DNA

Topic 5: DNA Blast

• NCBI blast 
• Gene sequence blast
• Protein blast

Topic 6 : Ranges into BioConductor

• Iranges
• Granges
• Granges plotting
• Granges w genes

Day 2

Topic 7: Visualizing Data in BioConductor

• Visualizing genomic features
• Visualizing DNA content
• Visualizing gene expression

Topic 8: Microarray Analysis

• Expression sets 
• Exploratory data analysis
• Clustering
• Linear Regression

Topic 9: NGS Analysis

• Working with shortread data
• Filtering sequences
• Matching and counting
• Visualizing NGS

Topic 10: Protein Analysis

• Read Fasta file
• Amino acid count
• Compute isoelectric and Mw
• Hydropathy scores

Topic 11: Visualizing Genomes

• ggbio package
• Visualizing karyograms
• Visualizing reference track
• Visualizing ideogram
• gvis package
• genomegraphs package

SSG Training Grant

SSG TG is $30 per pax. Net fee after SSG TG is $502.86. Absentee Payroll is not eligible.

Prerequisite

This is an intermediate course. the following basic knowledge is assumed

• R Programming
• Bioinformatics

Software Requirement

Please download and install the following software prior to the class

• R https://cran.r-project.org/
• R Studio https://www.rstudio.com/products/rstudio/download/

• Life Science Workers
• Bioinformatics Analysts

Dwight Nuwan Fonseka have a degree in Biotechnology (from NUS) ,Advanced diploma in Pharamceutical management (from MDIS) and Masters in Education (from NTU). He have 8 years experience of teaching biology at O and A levels/ IB level in international schools in Singapore and overseas.

Dr Brandon Ooi has a Bachelors degree in Computer Engineering and a PhD in Bioengineering from the National University of Singapore. He has published papers on machine learning, bioinformatics and microarray data analysis. He has six years of teaching experience at the polytechnic level and was also involved in the creation and teaching of modules for adult learners.

Dr. Marie Wong has a BSc (Biochemistry and Molecular Biology) from the University of Melbourne and a PhD (Structural Biology) from the University of Singapore. She has had more than 18 years in the field of Bioinformatics in both academic and industrial settings.

Dr Zheng Zejun has seven years’ experience in the data-mining field. Zejun worked as a (Sr.) bioinformatics scientist for six years and currently works as a data scientist manager. Dr. Zheng;s expertise covers machine learning, statistics, algorithm design, bioinformatics and high performance computing. He has published three machine learning algorithms on well-recognized academic journals together with the open source software (CUDA-CRISY, FSOM, DYSC). Zejun is professional with an extensive set of programming languages, including C/C++, Python, R, JAVA and flask for data driven analytics and scalable computing. He has also a broad knowledge of algorithms and mathematical models in the data-mining field.

Wesley Goi is currently in his final year of his PhD in Bioinformatics at National University of Singapore (NUS) where he previously received his degree in Molecular Biology at NUS (Honours 2nd Uppers). He was the TA for Introductory Bioinformatics LSM2241. He specialises in analysing high throughput DNA and RNA sequencing data of complex microbial communities using network analyses and various functional analyses. In his previous projects he has applied machine learning methods to vaccine discovery.